Algorithmic progress sustained by field expansion

The rapid rate of progress in language modeling is largely sustained by scaling up investment — doubling the size of the field each time difficulty doubles — which can continue for a while (hundreds to tens of thousands of researchers), but progress would slow if researcher numbers were held fixed as low-hanging fruit is exhausted.